code: def compute_common_stats(
      column,
  ) -> facet_feature_statistics_pb2.CommonStatistics:
      """
      Computes common statistics for a given column in the DataFrame.
  
      :param column: A column from a DataFrame.
      :return: A CommonStatistics proto.
      """
      common_stats = facet_feature_statistics_pb2.CommonStatistics()
      common_stats.num_missing = column.isnull().sum()
      common_stats.num_non_missing = (
          len(column) - common_stats.num_missing
      )
      # TODO: Add support to multi dimensional columns similar to
      # https://github.com/PAIR-code/facets/blob/4742b8b93c2dacf22fc8ace2cee42dd06382c48e/facets_overview/facets_overview/base_generic_feature_statistics_generator.py#L106-L117
      common_stats.min_num_values = 1
      common_stats.max_num_values = 1
      common_stats.avg_num_values = 1.0
  
      return common_stats
  
file_path: mlflow/mlflow/recipes/cards/pandas_renderer.py
imports: import base64
  import sys
  from typing import Iterable, Tuple, Union
  import numpy
  import pandas
  from packaging.version import Version
  from mlflow.exceptions import MlflowException
  from mlflow.protos import facet_feature_statistics_pb2
  from mlflow.recipes.cards import histogram_generator
label_desc: Use image node_id 3 for calling a global function with example usage: compute_common_stats(column) and returns: common_stats